As mobile terminals become more intelligent and popular, use of intelligent terminals is closely related to daily life of terminal users. In view of this, various application functions of the terminals are also gradually enhanced. Various application data of a user can be obtained by configuring an apparatus, such as a sensor, within the terminal; and a user activity can be recognized or forecasted according to these application data. Therefore, information is pushed to the user according to a forecast result, so as to improve using experience of the terminal user.
In the prior art, during recognition or forecast of a user activity, only application data of the terminal user can be collected by using a sensor, and the application data is matched to a preset activity classification model, thereby implementing recognition or forecast of the user activity. However, because an existing recognition or forecast manner is applicable to only application data of the user, where the number of data samples is limited, a recognition or forecast result is inaccurate, and a difference between information that is pushed to the user according to the recognition or forecast result and information in which the user is interested is comparatively large. As a result, using experience of the terminal user is not good.